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Association of Gaseous Ambient Air Pollution and Dementia-Related Neuroimaging Markers in the ARIC Cohort, Comparing Exposure Estimation Methods and Confounding by Study Site.
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- Author(s): Lynch, Katie M.; Bennett, Erin E.; Qi Ying; Eun Sug Park; Xiaohui Xu; Smith, Richard L.; Stewart, James D.; Duanping Liao; Kaufman, Joel D.; Whitsel, Eric A.; Power, Melinda C.
- Source:
Environmental Health Perspectives. Jun2024, Vol. 132 Issue 6, p067010-1-067010-14. 14p. - Source:
- Additional Information
- Subject Terms: NITROGEN oxide analysis; DEMENTIA risk factors; DIAGNOSIS of dementia; CARBON monoxide analysis; AIR pollution; RISK assessment; RESEARCH funding; LOGISTIC regression analysis; STATISTICAL sampling; BRAIN; MAGNETIC resonance imaging; DESCRIPTIVE statistics; LONGITUDINAL method; ODDS ratio; CEREBRAL cortex; OZONE; ENVIRONMENTAL exposure; NEURORADIOLOGY; CONFIDENCE intervals; DATA analysis software; BIOMARKERS; REGRESSION analysis
- Subject Terms:
- Abstract: BACKGROUND: Evidence linking gaseous air pollution to late-life brain health is mixed. OBJECTIVE: We explored associations between exposure to gaseous pollutants and brain magnetic resonance imaging (MRI) markers among Atherosclerosis Risk in Communities (ARIC) Study participants, with attention to the influence of exposure estimation method and confounding by site. METHODS: We considered data from 1,665 eligible ARIC participants recruited from four US sites in the period 1987–1989 with valid brain MRI data from Visit 5 (2011–2013). We estimated 10-y (2001–2010) mean carbon monoxide (CO), nitrogen dioxide (NO2), nitrogen oxides (NOx), and 8- and 24-h ozone (O3) concentrations at participant addresses, using multiple exposure estimation methods. We estimated site-specific associations between pollutant exposures and brain MRI outcomes (total and regional volumes; presence of microhemorrhages, infarcts, lacunes, and severe white matter hyperintensities), using adjusted linear and logistic regression models. We compared meta-analytically combined site-specific associations to analyses that did not account for site. RESULTS: Within-site exposure distributions varied across exposure estimation methods. Meta-analytic associations were generally not statistically significant regardless of exposure, outcome, or exposure estimation method; point estimates often suggested associations between higher NO2 and NOx and smaller temporal lobe, deep gray, hippocampal, frontal lobe, and Alzheimer disease signature region of interest volumes and between higher CO and smaller temporal and frontal lobe volumes. Analyses that did not account for study site more often yielded significant associations and sometimes different direction of associations. DISCUSSION: Patterns of local variation in estimated air pollution concentrations differ by estimation method. Although we did not find strong evidence supporting impact of gaseous pollutants on brain changes detectable by MRI, point estimates suggested associations between higher exposure to CO, NOx, and NO2 and smaller regional brain volumes. Analyses of air pollution and dementia-related outcomes that do not adjust for location likely underestimate uncertainty and may be susceptible to confounding bias. [ABSTRACT FROM AUTHOR]
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